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计算机系统应用:2018,27(10):11-21
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基于生物形状知识的人眼定位方法
方淑仙1,2, 张立武2
(1.中国科学院大学, 北京 100049;2.中国科学院 软件研究所, 北京 100190)
Eyes Location Method Based on Biometrics Shape Knowledge
FANG Shu-Xian1,2, ZHANG Li-Wu2
(1.University of Chinese Academy of Sciences, Beijing 100049, China;2.Institute of Software, Chinese Academy of Sciences, Beijing 100190, China)
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投稿时间:2018-03-13    修订日期:2018-04-03
中文摘要: 准确地定位出人眼位置并分离出虹膜、眼睑等区域对虹膜识别、人脸识别等生物特征识别技术具有重要意义.但是,在非理想环境下,人眼图像分辨率通常较低,并且容易受到光照条件、睫毛、阴影等噪声影响,对人眼区域进行正确分割是一项非常具有挑战性的工作.因此,本文针对姿态幅度较小的遮挡人眼图像分割存在的一些问题,利用Hough圆变换和形态学算法改进低分辨率下人眼的定位.该方法首先利用现有的人脸对齐方法分割出人眼感兴趣区域,采用双线性插值法对人眼图像进行预处理,去除镜面反射光斑;然后根据人眼图像中各区域的灰度分布规律,利用带约束的Hough圆检测算法定位出虹膜;之后结合全局动态阈值、局部自适应阈值及形态学算法分别定位出人眼上下眼睑,并利用最小二乘法拟合上下眼睑,最终分割出人眼虹膜、上下眼睑、巩膜等区域;最后在UBIRIS v1.0数据库及低分辨率人脸图像上对本文提出的算法进行测试.实验结果表明,本文提出的方法对实验室环境下高清虹膜图像及低分辨率人脸图像上的人眼定位均具有较强的鲁棒性.
Abstract:Locating human eye accurately and separating iris and eyelid is of great significance to biometric identification technology, such as iris recognition and face recognition. However, segmentation for the human eye under non-ideal environment is a very challenging job due to lower resolution of eye image, noises like superimposed occlusions of reflections, eyelashes, or shadows. In this study, in view of existing problems for unsheltered human eye image with small pose, we adopted circular Hough transform and morphological algorithm to improve the location of human eye in low resolution. Firstly, this method segments region of interest in face picture with existing face alignment method, and then makes use of bilinear interpolation to remove reflection in image processing module. Secondly, according to the gray distribution of human eye image, we utilize the constrained circular Hough transform to locate iris. Then, combined the global dynamic threshold method, local adaptive threshold method and morphological algorithm are used to locate upper and lower eyelids. After that, fit the eyelid using the least square method so as to cut apart the iris, sclera, upper and lower eyelids in human eye image. Finally, the proposed method was tested on low resolution face image in the wild and UBIRIS V1.0 iris images database released by University of Beira, Portugal. Experimental results demonstrate that the proposed algorithm has strong robustness for human eye location and segmentation in laboratory environment or for low resolution images in the wild.
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基金项目:国家自然科学基金(61472409)
引用文本:
方淑仙,张立武.基于生物形状知识的人眼定位方法.计算机系统应用,2018,27(10):11-21
FANG Shu-Xian,ZHANG Li-Wu.Eyes Location Method Based on Biometrics Shape Knowledge.COMPUTER SYSTEMS APPLICATIONS,2018,27(10):11-21

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